LIDAR Dynamic Resolution Circuitry for Memory Reduction
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Solution Overview
Problem
Conventional LIDAR imaging systems require high memory to achieve low uncertainty and wide ranging capabilities, which is inefficient and costly, especially when needing to resolve distances from 3 meters to 300 meters with less than 0.1% uncertainty.
Innovation Solution
The implementation of autonomous dynamic resolution (ADR) circuitry in LIDAR processing, which dynamically adjusts the time-to-digital converter (TDC) resolution and applies a data mask to selectively crop timestamp data, reducing memory requirements while maintaining the desired uncertainty across the entire measurement range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional LIDAR imaging systems use high memory capacity to achieve low uncertainty and wide ranging capabilities, then measurement precision and adaptability are improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent implements dynamic resolution adjustment where the LIDAR system automatically adapts its time resolution based on the measured distance to targets. For distant targets, higher resolution is applied; for close targets, lower resolution suffices. This dynamic adaptation eliminates the need for high memory capacity to handle all possible resolutions simultaneously, resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The system changes the time resolution parameter dynamically based on target distance. By adjusting the resolution parameter according to actual measurement needs rather than using a fixed high resolution for all cases, the system achieves low uncertainty when needed while reducing memory requirements overall
2Measurement precision
If conventional LIDAR imaging systems use high memory capacity to maintain low uncertainty across wide ranging distances, then measurement precision is improved, but ease of manufacture deteriorates
Solution Approach 1:
The dynamic resolution adjustment mechanism allows the system to use only the memory capacity necessary for actual measurement conditions. By adapting resolution to target distance, the system avoids over-provisioning memory, thereby reducing manufacturing cost while maintaining measurement precision when required
Solution Approach 2:
By changing the resolution parameter based on target distance, the system optimizes memory utilization. This parameter adaptation reduces the total memory capacity needed compared to a fixed high-resolution system, directly lowering manufacturing cost while preserving measurement precision for distant targets
3Measurement precision
If conventional LIDAR imaging systems use fixed high resolution for all ranging distances, then measurement precision is improved, but loss of information increases due to unnecessary data storage
Solution Approach 1:
The system dynamically adjusts resolution based on target distance, applying high resolution only when measuring distant targets where it is necessary for maintaining low uncertainty. For close targets, lower resolution is sufficient, eliminating unnecessary high-resolution data storage and reducing overall memory usage without compromising measurement precision when needed
4Ease of manufacture
If conventional LIDAR imaging systems reduce memory capacity to lower device complexity and cost, then ease of manufacture is improved, but adaptability deteriorates due to inability to handle wide ranging distances with low uncertainty
Solution Approach 1:
The dynamic resolution adjustment enables the system to adapt to different ranging distances with limited memory capacity. By switching between resolution levels based on target distance, the system maintains low uncertainty across the full ranging range (3-300 meters) without requiring high memory capacity for all resolutions simultaneously, thus preserving adaptability while reducing manufacturing cost
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces memory usage significantly while maintaining high accuracy and flexibility, allowing for high-resolution SPAD arrays in LIDAR systems, lowering manufacturing costs and die size, and enabling improved ranging capabilities without compromising frame rate or information integrity.
Implementation Method 1
Some imaging systems include image sensors that sense light by converting impinging photons into electrons or holes
Implementation Method 2
the light sensing diode is biased above its breakdown point, and when an incident photon generates an electron or hole, this carrier initiates an avalanche breakdown
Implementation Method 3
The LIDAR imaging system measures the return time of reflections off the target to determine a distance to the target
Data Source
AI summary
An imaging system may include a silicon photomultiplier with single-photon avalanche diodes (SPADs). The imaging system may be a LIDAR imaging system with LIDAR processing circuitry. To reduce memory requirements in the LIDAR processing circuitry, a dynamic resolution storage scheme may be used. The LIDAR processing circuitry may include autonomous dynamic resolution circuitry that receives input from a time-to-digital converter (TDC). The autonomous dynamic resolution circuitry may include a plurality of memory banks having different resolutions. Based on the magnitude of the input from the TDC, an appropriate memory bank may be selected. In parallel, an address encoder may select a memory bin based on the input from the TDC.